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Sponsored by the Robert Wood Johnson Foundation, the Active for Life (AFL) initiative investigated how two physical activity programs for adults aged 50 and older, Active Choices (AC) and Active Living Every Day (ALED), worked in community settings. Created by researchers at Stanford University, Active Choices used lifestyle counseling and personalized telephone support to encourage older adults to be physically active. In AFL, this was a 6-month program delivered through one face-to-face meeting followed by up to eight one-on-one telephone counseling calls. Active Living Every Day, which was created by the Cooper Institute and Human Kinetics Inc., also provided lifestyle counseling to promote physical activity, but in a classroom and workbook format. During the first three years of the four-year AFL initiative, ALED was delivered as a 20-week program where participants attended weekly small group meetings, but in the last year it was shortened to 12 weekly meetings. Nine organizations received AFL grants to implement the programs during 2003-2006. Four grantees implemented the one-on-one AC model, while five implemented the group-based ALED model.

Data were collected from the AC and ALED sites for both a process and outcomes evaluation. The primary aims of the process evaluation were to (1) monitor the extent to which the grantees demonstrated fidelity to the AC and ALED models in their program implementation, (2) assess staff experiences implementing the programs, and (3) assess participants' impressions of the programs. A quasi-experimental, pre-post study design was used to assess outcomes. Primary aims of the outcomes evaluation were to evaluate the impact of AC and ALED on self-reported physical activity, and to evaluate the impact of the programs on self-reported stress, depressive symptoms, and satisfaction with body function and appearance. Secondary aims of the outcome evaluation were to (1) evaluate the impact of the programs on measures of functional fitness, (2) examine whether changes in self-reported physical activity and functional fitness were moderated by participant characteristics, including age, gender, race, baseline physical activity self-efficacy, and baseline physical activity social support, and (3) examine whether changes in self-reported physical activity were consistent with a mediation model for physical activity self-efficacy and physical activity social support.

The collection has 14 data files (datasets). Datasets 1-7 constitute the process evaluation data, and Datasets 8-14 the outcomes evaluation data:

Dataset 1 (AC Initial Face-to-Face Sessions Data) contains information about the initial face-to-face AC session: the format, date, and length of the session, whether the 8 steps required in the face-to-face session were completed, what was discussed between the health educator and the participant related to physical activity plans, interests, benefits, and barriers, and the health educator's progress notes. The file contains one record for each AC participant.

Dataset 2 (AC Completed Calls Data) comprises information about the completed AC calls, but does not cover the topics discussed on the calls. Recorded information about each call includes the date and length of the call, the health educator's progress notes, and whether the participant was assessed for injury, light activity, moderate activity, exercise goals, or exercise intentions. Each call is represented by a separate record in the data file and, typically, there are multiple records per participant.

Dataset 3 (AC Topics Discussed on Completed Calls ) contains information about the topics discussed on each completed AC call, e.g., exercise barriers/benefits, previous exercise experiences, goal setting, long term goals, injury prevention, rewards/reinforcement, social support, progress tracking, and relapse prevention. Each record in the file represents one topic and there are often multiple records per call for each participant.

Dataset 4 (AC Aggregate Call Data) aggregates the call data across calls for each AC participant. For example, for a given participant, this dataset shows the total number of calls completed, the number of calls where injury/health problems were assessed, etc. The file contains one record per participant.

Dataset 5 (ALED Sessions Data) contains information about each class session for every ALED group, including the session date, start time, and end time, learning activities covered in the session, participant evaluations of the session and the facilitator, facilitator progress notes, the number of participants who were in various stages of readiness for moderate exercise, and the number of participants who tracked physical activity and thoughts about physical activity. This file has one record for each session of every ALED group.

Dataset 6 (ALED Attendance and Tracking Data (Years 2-4)) consists of participant-level attendance and tracking data for every ALED session during the second to fourth years of the evaluation, including the participant's attendance at the session, whether the participant's stage of readiness was assessed, and whether the participant tracked thoughts about physical activity or actual physical activity. There is no participant-level ALED data for the first year. Each participant has a separate record for each session. Thus, the file contains 20 records per participant in the years 2-3, and 12 records per participant in year 4.

Dataset 7 (ALED Aggregate Attendance and Tracking Data (Years 2-4)) contains ALED attendance and tracking data for each participant in years 2-4, aggregated across the sessions. The data file has one record for each participant.

Dataset 8 (Demographics) comprises program information (e.g., program status, start date, end date, site, etc.), demographic information (e.g., age, gender, race, Hispanic origin, employment status, income, and the participant's state and ZIP code of residence), and responses to the Physical Activity Readiness Questionnaire (PAR-Q), a screening tool that was used to assess possible risks of exercising based on answers to specific health history questions. The file contains one record for each AFL participant, except for those with a status of "nonstarter" or "repeater."

Datasets 9 (Pretest Survey Data) and 10 (Posttest Survey Data) contain data from the Pretest and Posttest Surveys. The Pretest Survey was administered at the beginning of the AC and ALED programs, while the Posttest Survey was administered at their end. Topics covered by the surveys include social and recreational activities, activities undertaken for exercise, perceived stress, depressive symptoms, satisfaction with body appearance and function, social support for physical activity, self-efficacy for physical activity, neighborhood environment, health conditions, health-related quality of life, caregiving, and self-reported height and weight. Both surveys included items from the Community Health Activities Model Program for Seniors Physical Activity Questionnaire (CHAMPS), the Center for Epidemiological Studies Depression Questionnaire (CES-D), the Behavioral Risk Factor Surveillance System Questionnaires (BRFSS), and the International Physical Activity Prevalence Study Environmental Module. These data files each have one record for each participant who submitted a questionnaire.

Dataset 11 (ALED Week 12 Survey Data (Year 4)) contains responses to the ALED Week 12 Posttest Survey, which was used to evaluate the 12-week adaptation of ALED in Year 4. (In Year 4, ALED participants completed both a 12- and 20-week posttest survey). There is one record for each participant who returned this survey.

Dataset 12 (Six-Month Posttest Follow-Up Survey Data (Years 3-4)) comprises data from a special 6-month follow-up survey which was administered in years 3-4 in six of the ALED sites and one of the AC sites. Participants were questioned about their current physical activities, weight, health-related quality of life, satisfaction with bodily function, and other topics. As with Datasets 9-11, the data file contains one record for each participant who returned a questionnaire.

Dataset 13 (Functional Fitness Tests Data) contains the results of pretest and posttest functional fitness tests which were administered by one ALED grantee. Four tests were adminstered: (1) the 30-Foot Walk Test, (2) the 30-Second Chair Stand, (3) 8-Foot Up and Go, and (4) the Chair Sit and Reach Test. This participant-level data file also includes pretest height measurements plus pretest and posttest weight measurements.

Dataset 14 (Participants' Impressions of the Programs (Years 1, 3, and 4)) contains data collected by the last sections of the Posttest Survey, ALED Week 12 survey, and 6-Month Follow-up Survey. The topics it covers include the participants' impressions of the programs, participation in physical activities, and changes (compared to before they started the AFL program) in motivation to be physically active, actual level of physical activity, medical and health conditions, overall pain, flexibility/limberness, level of stress, happiness, and enjoyment of life. The file has a separate record for each survey completed by the participants. Thus, there are 1-3 records per participant.

Mother and Infant Home Visiting Program Evaluation-Strong Start (MIHOPE-Strong Start) was a large-scale evaluation that rigorously tested the effectiveness of evidence-based home visiting in improving birth and health outcomes during pregnancy and in the year after birth. Local programs included in the study's analysis implemented one of two evidence-based models: Healthy Families America (HFA) or Nurse-Family Partnership (NFP). These models were chosen because earlier evaluations found some evidence of their having positive impacts on birth outcomes.

The Office of Planning, Research, and Evaluation (OPRE) of the Administration for Children and Families (ACF) partnered with the Center for Medicare and Medicaid Innovation (CMMI) of the Centers for Medicare and Medicaid Services (CMS) and the Maternal and Child Health Bureau (MCHB) of the Health Resources and Services Administration (HRSA) to sponsor the study. MIHOPE-Strong Start was part of the CMMI's Strong Start for Mothers and Newborns Initiative, which evaluated whether enhanced, nonmedical prenatal interventions, when provided in addition to routine medical care, have the potential to improve birth outcomes and reduce health care costs for women enrolled in Medicaid or the Children's Health Insurance Program (CHIP). Under contract with OPRE, MDRC conducted MIHOPE-Strong Start in collaboration with James Bell Associates, Johns Hopkins University, Mathematica, and New York University.

The analysis for MIHOPE-Strong Start included 2,899 women and 66 local programs (37 HFA and 29 NFP programs) operating across 17 states: California, Georgia, Illinois, Indiana, Iowa, Kansas, Massachusetts, Michigan, Nevada, New Jersey, New York, North Carolina, Pennsylvania, South Carolina, Tennessee, Washington, and Wisconsin. Women were eligible for MIHOPE-Strong Start if they were pregnant and at least 8 weeks from their due date.

The MIHOPE-Strong Start analysis included a subset of families and local programs that were recruited for MIHOPE, the national evaluation of the Maternal, Infant, and Early Childhood Home Visiting (MIECHV) program. Specifically, the MIHOPE-Strong Start impact analysis included information on 46 local home visiting programs and 1,845 families that were initially recruited for MIHOPE but met the MIHOPE-Strong Start eligibility criteria. An important distinction between MIHOPE-Strong Start and MIHOPE is that MIHOPE included only programs receiving MIECHV funding, while MIHOPE-Strong Start included both MIECHV and non-MIECHV-funded programs.

In both studies, families were randomly assigned either to an evidence-based home visiting program or to a control group who was given information on other services available in the community. The random assignment design was intended to create program and control groups that were similar when women entered the study, so that systematic differences in the outcomes of interest observed between the two groups can be attributed to the home visiting services rather than to the preexisting characteristics of the women.

The purpose of the study was to assess the impact of Latino ethnicity on pretrial release decisions in large urban counties. The study examined two questions:

• Are Latino defendants less likely to receive pretrial releases than non-Latino defendants?
• Are Latino defendants in counties where the Latino population is rapidly increasing less likely to receive pretrial releases than Latino defendants in counties where the Latino population is not rapidly increasing?

The study utilized the State Court Processing Statistics (SCPS) Database (see STATE COURT PROCESSING STATISTICS, 1990-2004: FELONY DEFENDANTS IN LARGE URBAN COUNTIES [ICPSR 2038]). The SCPS collects data on felony cases filed in state courts in 40 of the nation's 75 largest counties over selected sample dates in the month of May of every even numbered year, and tracks a representative sample of felony case defendants from arrest through sentencing. Data in the collection include 118,556 cases.

Researchers supplemented the SCPS with county-level information from several sources:

• Federal Bureau of Investigation Uniform Crime Reporting Program county-level data series of index crimes reported to the police for the years 1988-2004 (see UNIFORM CRIME REPORTS: COUNTY-LEVEL DETAILED ARREST AND OFFENSE DATA, 1998 [ICPSR 9335], UNIFORM CRIME REPORTING PROGRAM DATA [UNITED STATES]: COUNTY-LEVEL DETAILED ARREST AND OFFENSE DATA, 1990 [ICPSR 9785], 1992 [ICPSR 6316], 1994 [ICPSR 6669], 1996 [ICPSR 2389], 1998 [ICPSR 2910], 2000 [ICPRS 3451], 2002 [ICPSR 4009], and 2004 [ICPSR 4466]).
• Bureau of Justice Statistics Annual Survey of Jails, Jurisdiction-Level data series for the years 1988-2004 (see ANNUAL SURVEY OF JAILS: JURISDICTION-LEVEL DATA, 1990 [ICPSR 9569], 1992 [ICPSR 6395], 1994 [ICPSR 6538], 1996 [ICPSR 6856], 1998 [ICPSR 2682], 2000 [ICPSR 3882], 2002 [ICPSR 4428], and 2004 [ICPSR 20200]).
• Bureau of Justice Statistics National Prosecutors Survey/Census data series 1990-2005 (see NATIONAL PROSECUTORS SURVEY, 1990 [ICPSR 9579], 1992 [ICPSR 6273], 1994 [ICPSR 6785], 1996 [ICPSR 2433], 2001 census [ICPSR 3418], and 2005 [ICPSR 4600]).
• United States Census Bureau State and County Quickfacts.
• National Center for State Courts, State Court Organization reports, 1993 (see NCJ 148346), 1998 (see NCJ 178932), and 2004 (see NCJ 212351).
• Bureau of Justice Statistics Felony Defendants in Large Urban Counties reports, 1992 (see NCJ 148826), 1994 (see NCJ 164616), 1996 (see NCJ 176981), 1998 (see NJC 187232), 2000 (see NCJ 202021), and 2002 (see NJC 210818).

The data include defendant level variables such as most serious current offense charge, number of charges, prior felony convictions, prior misdemeanor convictions, prior incarcerations, criminal justice status at arrest, prior failure to appear, age, gender, ethnicity, and race. County level variables include region, crime rate, two year change in crime rate, caseload rate, jail capacity, two year change in jail capacity, judicial selection by election or appointment, prosecutor screens cases, and annual expenditure on prosecutor's office. Racial threat stimuli variables include natural log of the percentage of the county population that is Latino, natural log of the percentage of the county population that is African American, change in the percentage of the county population that is Latino over the last six years and change in the percentage of the county population that is African American over the last six years. Cross-level interaction variables include percentage minority (Latino/African American) population zero percent to 15 percent, percentage minority (Latino/African American) population 16 percent to 30 percent, and percentage minority (Latino/African American) population 31 percent or higher.